code: def test_maxit_None():
      """Check lobpcg if maxit=None runs 20 iterations (the default)
      by checking the size of the iteration history output, which should
      be the number of iterations plus 2 (initial and final values).
      """
      np.random.seed(1566950023)
      n = 50
      m = 4
      vals = -np.arange(1, n + 1)
      A = diags([vals], [0], (n, n))
      A = A.astype(np.float32)
      X = np.random.randn(n, m)
      X = X.astype(np.float32)
      _, _, l_h = lobpcg(
          A, X, tol=1e-8, maxiter=20, retLambdaHistory=True
      )
      assert_allclose(np.shape(l_h)[0], 20 + 2)
  
imports: import itertools
  import platform
  import numpy
  from numpy.testing import assert_almost_equal, assert_equal, assert_allclose, assert_array_less
  import pytest
  from numpy import ones, r_, diag
  from numpy.random import rand
  from scipy.linalg import eig, eigh, toeplitz, orth
  from scipy.sparse import spdiags, diags, eye
  from scipy.sparse.linalg import eigs, LinearOperator
  from scipy.sparse.linalg.eigen.lobpcg import lobpcg
label_desc: Use image node_id 18 for calling a global function with example usage: test_maxit_None() without return types